4.7 Review

Data collection methods for studying pedestrian behaviour: A systematic review

Journal

BUILDING AND ENVIRONMENT
Volume 187, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.buildenv.2020.107329

Keywords

Pedestrian behaviour; Data collection method; Literature review; Virtual reality; Crowd; IoT

Funding

  1. China Scholarship Council
  2. ALLEGRO project - European Research Council [669792]
  3. European Research Council (ERC) [669792] Funding Source: European Research Council (ERC)

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This systematic review of 145 studies highlights the imbalance in pedestrian behaviour research, particularly in large complex scenarios and high-risk situations. It also points out issues with current research, such as lack of comprehensive data sets, limited generalizability, and high experimental costs. The review identifies potential solutions through the adoption of new technologies like VR experiments, large-scale crowd monitoring, and the Internet of Things to advance pedestrian behaviour research.
Collecting pedestrian behaviour data is vital to understand pedestrian behaviour. This systematic review of 145 studies aims to determine the capability of contemporary data collection methods in collecting different pedestrian behavioural data, identify research gaps and discuss the possibilities of using new technologies to study pedestrian behaviour. The review finds that there is an imbalance in the number of studies that feature various aspects of pedestrian behaviour, most importantly (1) pedestrian behaviour in large complex scenarios, and (2) pedestrian behaviour during new types of high-risk situations. Additionally, three issues are identified regarding current pedestrian behaviour studies, namely (3) little comprehensive data sets featuring multidimensional behaviour data simultaneously, (4) generalizability of most collected data sets is limited, and (5) costs of pedestrian behaviour experiments are relatively high. A set of new technologies offers opportunities to overcome some of these limitations. This review identifies three types of technologies that can become a valuable addition to pedestrian behaviour research methods, namely (1) applying VR experiments to study pedestrian behaviour in the environments that are difficult or cannot be mimicked in real-life, repeat experiments to determine the impact of factors on pedestrian behaviour and collect more accurate behavioural data to understand the decision-making process of pedestrian behaviour deeply, (2) applying large-scale crowd monitoring to study pedestrian movements in large complex environments and incident situations, and (3) utilising the Internet of Things to track pedestrian movements at various locations that are difficult to investigate at the moment.

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